How we are using AI and Agents to support community organizations

Across YMCAs, community centers, and parks and recreation organizations, conversations about AI are becoming more common. Leaders are curious, but also careful. They are responsible for their teams, their communities, and the trust placed in their organizations.

In our conversations with leaders, the question is rarely whether AI is possible. It is whether it is practical, responsible, and genuinely helpful in day-to-day operations.

What AI looks like when it is actually useful

Leaders are not asking for more technology. They are asking for fewer interruptions. Clearer signals. And systems that make the routine parts of the job easier.

AI gets a lot of attention right now, but much of the conversation focuses on what is possible rather than what is practical. At Traction Rec, our focus has been simpler: applying AI in specific places where it can quietly remove friction and support everyday work.

These capabilities are not conceptual. They are built into the Traction Rec platform and are already being used by customers today. What follows is a look at how we are applying AI and agents now, and what we are learning as organizations begin to adopt them.

Making registration easier for families and quieter for staff

Registration is one of the most visible pressure points across community organizations. Families want quick answers and clear guidance. Staff often find themselves answering the same questions again and again, especially during the busiest parts of the day.

Some Traction Rec customers are now using a registration agent to support their communities directly.

The agent allows people to ask questions in plain language, search program catalogs, and complete registrations using personalized information from their account history. It handles common complexities like multiple children in a household, age-based eligibility, and overlapping schedules.

What has stood out most is how quickly teams begin to adjust once the agent is live.

As real families interact with it, organizations can see where questions cluster, what information needs to be clearer, and how self-service can better support their community. Many teams are already iterating on workflows based on this insight.

In practice, this has meant:

• More questions answered after hours
• Fewer routine interruptions for frontline staff
• A smoother experience for families who just want to sign up and move on with their day

The goal is not to replace human interaction. It is to handle the repeatable questions well, so staff have more space for the moments that actually require a person.

Helping staff get answers without slowing down

Some of the most meaningful impact of AI happens behind the scenes. At Traction Rec, we are using AI agents to help customers find what they need more quickly across documentation, training resources, and knowledge articles.

Instead of digging through multiple systems or submitting a support ticket, users can ask a question and get an answer immediately. When something truly requires human support, that path is still there. The difference is how often it is needed.

Within the first months of using this internally, we have already seen a noticeable drop in support cases created. Adoption has been fast, and the feedback has been especially telling.

Customers have shared reactions like:

“The Community Support Agent is my new best friend. I haven’t needed to submit a single case since it launched.”

Others have highlighted how valuable this is for learning and confidence:

“I really love it and can’t stress enough how helpful it has been for me. I’m a Salesforce admin and still learning, and the agent in the success community has been a game changer.”

And for many, the power lies in how information is brought together:

“I love that it can gather information from different sources to answer the question.”

What we are learning is that speed to clarity matters. When staff can get answers quickly, they feel more confident using the system, onboarding improves, and support teams can focus on more complex issues instead of repeating the same answers.

Using predictive analytics to see what is coming sooner

AI is not only about automation. It is also about attention. Traction Rec leverages Salesforce’s predictive analytics and machine learning to help organizations spot patterns earlier and focus their efforts where they matter most.

These insights can highlight:

• Members or participants who may be at risk of disengaging
• Individuals who may be more likely to donate or deepen involvement
• Programs that may need attention before participation declines
• Shifts in engagement that deserve a closer look

The value here is not certainty. It is timing.

Instead of learning about an issue after it appears in a report, leaders get earlier signals that prompt questions and conversations. Human judgment remains central. The data simply helps teams look in the right places sooner.

Built in, not bolted on

One thing we care deeply about is how these tools fit into the broader system.

Because AI and agents are built directly into the Traction Rec platform on Salesforce, they operate within existing security, data governance, and permission structures. Recommendations support staff decisions rather than override them, and organizations remain in control of how AI is used.

For community organizations built on trust, that foundation matters as much as the features themselves.

What we are learning along the way:

• As customers continue to adopt and experiment with these tools, a few themes keep showing up.
• AI is most helpful when it starts with repetitive, predictable work
• Adoption grows when tools feel intuitive and trustworthy
• The biggest wins often come from removing friction, not adding complexity

Most importantly, progress happens fastest when these capabilities evolve alongside real users, informed by real behavior.

Continuing to build with community organizations

This work is ongoing, and we see it as a partnership.

We will continue refining how AI and agents are used within Traction Rec, guided by what community organizations actually need and how they work day to day. The goal is not to lead with technology, but to support the people behind the programs, memberships, and services that bring communities together.

For organizations actively evaluating platforms, seeing these capabilities in context often matters more than reading about them. If you’d like to explore how AI and agents are used within Traction Rec in more detail, our team is happy to share examples and walk through what’s live today.